Robust Test for Genetic Effect in Presence of Interaction with Age-At-First-Drink

描述（由申请人提供）： 多项流行病学研究表明，酒精依赖是一种受遗传和环境因素影响的复杂行为障碍。因此，在其遗传关联设计中增加有关环境暴露的信息是推荐的适当策略，原因如下。首先，遗传和环境因素之间的相互作用的知识是必不可少的酒精依赖的病因学的完整理解。其次，解释由于相互作用而导致的遗传效应的异质性对于关联检验中的主要假设的有效性和增强的功效是至关重要的。最常被引用的酒精依赖风险的环境因素是首次饮酒的年龄。这种关联在许多流行病学研究中得到证实，表明未成年人饮酒与酒精参与和依赖增加有关。最近的双胞胎研究表明，第一次饮酒的年龄缓和了酒精依赖的遗传影响。因此，在关联研究中，首次饮酒的年龄是遗传脆弱性的环境修饰剂的理想候选者。在存在连续的环境暴露的情况下，研究者需要仔细选择因子与酒精依赖的比值比对数之间的关联的函数形式。否则，错误指定的主效应将导致遗传关联的标准logistic回归tess中1型错误率的急剧膨胀。还有压倒性的证据证实了家庭影响对首次饮酒年龄的作用，这表明存在基因-环境关联。因此，利用基因-环境独立性（即仅病例）且不需要指定环境的主要影响的测试容易受到偏倚结果的影响，因此不能使用。为了放松风险与暴露之间的参数关系的假设，以及减少其错误设定的戏剧性影响，非参数项被引入到模型中。使用分数检验方法来避免一般非参数模型下与参数估计相关的数值困难。由此产生的测试很容易实现，它们保持了所需的类型1错误级别。此外，当遗传和环境因素之间存在相互作用时，拟议的测试获得了相当大的力量，而当没有相互作用时，则几乎没有损失。所提出的方法将被应用于收集的数据作为成瘾研究的一部分：遗传学和环境（SAGE）可通过基因型和表型数据库（dbGaP）。然而，拟议方法的灵活性以及软件的可用性将使 适应其他遗传关联研究与持续的环境暴露。

DESCRIPTION (provided by applicant): Multiple epidemiological studies imply that alcohol dependence is a complex behavioral disorder influenced by both genetic and environmental factors. Hence, to add information about environmental exposure to its genetic association designs is the appropriate strategy recommended for the following reasons. First, the knowledge of the interplay between genetic and environmental factors is essential for a complete understanding of the etiology of alcohol dependence. Second, accounting for heterogeneity of genetic effects due to interaction can be vital for the validity and enhanced power of the primary hypothesis in association testing. The most commonly cited environmental contributor to risk of alcohol dependence is age at first drink. This association replicated in many epidemiological studies suggests that underage drinking is linked to increased alcohol involvement and dependence. Twin studies have recently demonstrated that age at first drink moderates genetic influences on alcohol dependence. Therefore, age at first drink is an ideal candidate for an environmental modifier of genetic vulnerability in association studies. In the presence of a continuous environmental exposure, the investigator needs to carefully select the functional form of the association between the factor and the logarithm of the odds ratio of alcohol dependence. Otherwise, the misspecified main effect would lead to a dramatic inflation of Type 1 error rates in standard logistic regression tess of genetic associations. There is also overwhelming evidence that confirms the role of familial influences on age at first drink, which suggests the presence of gene-environment association. Hence tests that exploit gene-environment independence (i.e. case-only) and do not require that the main effect of the environment be specified, are susceptible to biased results and cannot be used. To relax the assumption about a parametric relationship between risk and exposure as well as reduce the dramatic effects of its misspecification, a nonparametric term is introduced into a model. Score testing approach is used to avoid numerical difficulty associated with parameter estimation under general nonparametric models. The resulting tests are straightforward to implement, they maintain the desired Type 1 error level. Moreover, the proposed tests gain substantial power when there is an interaction between genetic and environmental factors and lose little power when there is none. The proposed methodology will be applied to the data collected as part of Study of Addiction: Genetics and Environment (SAGE) available through the database of Genotypes and Phenotypes (dbGaP). However, flexibility of the proposed methodology as well as availability of the software will result in easy adaptation to other genetic association studies with a continuous environmental exposure.